Dr. Benjamin Eysenbach

Biography

Eysenbach joined Princeton faculty in 2023. His research aims to develop principled reinforcement learning algorithms that achieve state-of-the-art performance with higher simplicity, scalability, and robustness than current methods. His work utilizes ideas from probabilistic inference to make progress on important problems in reinforcement learning, such as long-horizon high-dimensional reasoning, robustness, and exploration. He completed his Ph.D. in machine learning at Carnegie Mellon University after spending several years at Google Brain/Research. He obtained his undergraduate degree in mathematics from the Massachusetts Institute of Technology.

Research Interests

Experience